neurodevelopmental profile of fetal alcohol spectrum disorder: a … · 2017. 8. 26. · (fas),...

RESEARCH ARTICLE Open Access

Neurodevelopmental profile of FetalAlcohol Spectrum Disorder: A systematicreviewShannon Lange1,2*, Joanne Rovet3,4, Jürgen Rehm1,2,5,6 and Svetlana Popova1,2,5,7

Abstract

Background: In an effort to improve the screening and diagnosis of individuals with Fetal Alcohol Spectrum Disorder(FASD), research has focused on the identification of a unique neurodevelopmental profile characteristic of thispopulation. The objective of this review was to identify any existing neurodevelopmental profiles of FASD and reviewtheir classification function in order to identify gaps and limitations of the current literature.

Methods: A systematic search for studies published up to the end of December 2016 reporting an identifiedneurodevelopmental profile of FASD was conducted using multiple electronic bibliographic databases. The search wasnot limited geographically or by language of publication. Original research published in a peer-reviewed journal thatinvolved the evaluation of the classification function of an identified neurodevelopmental profile of FASD wasincluded.

Results: Two approaches have been taken to determine the pathognomonic neurodevelopmental features of FASD,namely the utilization of i) behavioral observations/ratings by parents/caregivers and ii) subtest scores from standardizedtest batteries assessing a variety of neurodevelopmental domains. Both approaches show some promise, with the formerapproach (which is dominated by research on the Neurobehavioral Screening Tool) having good sensitivity (63% to 98%),but varying specificity (42% to 100%), and the latter approach having good specificity (72% to 96%), but varying sensitivity(60% to 88%).

Conclusions: The current review revealed that research in this area remains limited and a definitive neurodevelopmentalprofile of FASD has not been established. However, the identification of a neurodevelopmental profile will aidin the accurate identification of individuals with FASD, by adding to the armamentarium of clinicians. The fullreview protocol is available in PROSPERO (http://www.crd.york.ac.uk/PROSPERO/); registration numberCRD42016039326; registered 20 May 2016.

Keywords: Classification accuracy, Fetal Alcohol Spectrum Disorder, Neurodevelopmental profile, Prenatalalcohol exposure, Systematic review

BackgroundFetal Alcohol Spectrum Disorder (FASD) is a term thatencompasses a range of disorders, all of which involveprenatal alcohol exposure as the etiological cause. Theeffects of prenatal alcohol exposure can vary from mildto severe, and can include a broad array of cognitive,

behavioral, emotional, adaptive functioning deficits, aswell as congenital anomalies. FASD includes the follow-ing alcohol-related diagnoses: Fetal Alcohol Syndrome(FAS), Partial FAS (pFAS), Alcohol-Related Neurodeve-lopmental Disorder (ARND), and depending on thediagnostic guideline, Alcohol-Related Birth Defects(ARBD; [1, 2]). Recently, it has been proposed thatFASD be used as a diagnostic term with the specificationof the presence or absence of the sentinel facial features,rather than simply a non-diagnostic umbrella term [3].This is in line with the Diagnostic and Statistical Manual

* Correspondence: [email protected] for Mental Health Policy Research, Centre for Addiction and MentalHealth , Toronto, ON, Canada2Institute of Medical Science, University of Toronto, Toronto, ON, CanadaFull list of author information is available at the end of the article

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of Mental Disorders, Fifth Edition (DSM-5; [4]) whereNeurobehavioral Disorder Associated with PrenatalAlcohol Exposure (ND-PAE) was included as a conditionthat warrants further research and also as one specifierfor the broader diagnostic term of Other SpecifiedNeurodevelopmental Disorder. ND-PAE is intended toencompass the behavioral, developmental and mentalhealth symptoms associated with prenatal alcohol expos-ure and is appropriate for individuals with or withoutphysical findings [5].With the exception of ARBD, all of the disorders within

the spectrum are associated with a broad array of neuro-developmental deficits [6–9]. Specifically, individuals withFASD exhibit relative deficits in adaptive function,attention, executive function, externalizing behaviors,motor function, social cognition, and verbal and nonverballearning [10, 11].Until very recently, the specific domains of function to

be evaluated during the neurodevelopmental assessmenthave been relatively undefined and have lacked consen-sus [12]. The diagnostic guidelines have had a tendencyto focus on the severity of the neurodevelopmentalimpairments rather than the specificity of the impair-ments. This weakness of the former diagnosticguidelines mainly impacted the diagnosis of ARND,given that diagnosis is based primarily on the neurode-velopmental impairments the child exhibits as thecharacteristic facial traits and growth deficits associatedwith FAS and pFAS are often absent with ARND. Yet,ARND is recognized to be the largest category ofaffected individuals, representing as many as 80–90% ofFASD cases [13]. In addition to the ambiguity surround-ing the diagnosis of FASD, the neurodevelopmentalassessment is thought to be the lengthiest and mostcumbersome component of the diagnostic evaluation[14]. Following the revised clinical guidelines of Hoymeand colleagues [2] and the proposed criteria for ND-PAE[5], three primary domains of functional impairmenthave been identified, namely neurocognition, self-regulation and adaptive functioning. Nevertheless, moreinformation is needed regarding the validity of theavailable diagnostic approaches and the suggestedcut-points.Further, coupled with the fact that the signs of such

conditions as traumatic head injury and intellectualdisability where the etiological cause is not prenatal alco-hol exposure are similar to FASD, the diagnostic criteriaof FASD may also overlap with other neurodevelopmen-tal disorders such as Attention Deficit HyperactivityDisorder (ADHD), Oppositional Defiant Disorder(ODD), and Conduct Disorder (CD) [15]. As a result,individuals with FASD often receive multiple diagnosesbefore actually being assessed for and diagnosed withFASD [16]. It is important to note that diagnostic

misclassification can have a number of untoward conse-quences, particularly inappropriate treatments and inter-ventions, mismanagement of behavioral symptoms,inaccurate incidence and prevalence estimates, andreduced ability to detect a significant difference betweendiagnostic groups in clinical research studies [16, 17].Therefore, in an effort to improve the screening and

diagnosis of individuals with FASD, most research to datehas focused on the identification of a distinct neurodeve-lopmental profile of FASD – defined as the outwardexpression (behavioral and developmental) of the centralnervous system damage caused by prenatal alcohol expos-ure. The notion that a distinctive neurodevelopmentalprofile exists in individuals with FASD first emerged inthe late 1990s by Stressiguth and colleagues [18].However, identifying a neurodevelopmental profileremains to be a challenge given the wide range of deficitsindividuals with FASD exhibit, as well as the fact that theirdeficits may overlap with other neurodevelopmentaldisorders. Moreover, in order to determine how well aprofile can accurately identify individuals with FASD, itmust be tested in a diverse population and also be bothsensitive and specific.1

In order to identify gaps and limitations of theexisting literature, the current review aimed to i)identify existing neurodevelopmental profiles of FASDand ii) review the classification function (the ability ofa profile to determine to which group each case mostlikely belongs – i.e., the sensitivity and specificity) ofthe respective profiles. As such, the current review islimited to those profiles for which their classificationfunction, as a binary classification test, has beenevaluated.

MethodsComprehensive systematic literature searchThe systematic literature search was conducted and re-ported according to the standards set out in PreferredReporting Items for Systematic Reviews and Meta-Analyses[19]. A systematic literature search was performed to iden-tify all studies that have identified a neurodevelopmentalprofile of FASD and were published between November 1,1973, when FAS was first described [20], and December 30,2016. The search was conducted in multiple electronicbibliographic databases, which included: CINAHL, Embase,ERIC, Medline, Medline in process, PsychINFO, Scopusand Web of Science (including Arts and HumanitiesCitation Index, Science Citation Index, and Social SciencesCitation Index). The following key words were used: 1) al-cohol* embryopath*, alcohol* related* neurodevelopmental*disorder*, alcohol* related* birth defect*, arnd, arbd, fetal*alcohol* effect*, fae, fas, fasd, fetal alcohol syndrome*, fetalalcohol spectrum disorder*, foetal* alcohol* effect, foetal*alcohol syndrome*, foetal* alcohol spectrum disorder*, pfas,

Lange et al. BMC Psychology (2017) 5:22 of 12

partial fetal alcohol syndrome, partial foetal alcohol syn-drome, prenatal* alcohol expos*, OR pre-natal* alcoholexpos*; AND 2) behavio*, cogniti*, development*, neurobe-havio*, neurocogniti*, neurodevelopment*, neuropsycho-log*, OR psycholog*; AND 3) profile*, phenotype*, ORprofile analysis. The search was not limited geographicallyor by language of publication. Manual reviews of the con-tent pages of the major journals in the field of neurodeve-lopmental disorders were conducted, as well as citations inany of the relevant articles. The full review protocol is avail-able in PROSPERO (http://www.crd.york.ac.uk/PROS-PERO/), registration number CRD42016039326.

Inclusion and exclusion criteriaArticles were included if they were full-text articles (i.e.,conference abstracts were excluded) consisting of ori-ginal, quantitative research published in a peer-reviewedjournal that identified a neurodevelopmental profile ofFASD. Articles were excluded if they did not involve anevaluation of the classification function of the identifiedneurodevelopmental profile of FASD.

Data selection and extractionStudy selection began by screening titles and abstractsfor inclusion. Then, full-text articles of all studiesscreened as potentially relevant were considered. Alldata were extracted by one investigator and then inde-pendently crosschecked by a second investigator for ac-curacy against the original studies. All discrepancieswere reconciled by team discussion.

UncertaintyIn order to estimate the level of uncertainty surroundingthe classification estimates, exact 95% confidence inter-vals (CI) were estimated using a binomial distribution.

ResultsInitially, the search strategy yielded a total of 768records. After removing 325 duplicates, a total of 443 re-cords were screened using titles and abstracts. Forty-sixfull-text articles were retrieved for further consideration,37 of which were subsequently excluded. This left a totalof nine studies, all in English, that met the inclusion cri-teria and were retained for review. A schematic diagramof the search strategy is depicted in Fig. 1.Based on the identified studies, two general ap-

proaches were observed for determining the pathogno-monic neurodevelopmental features of FASD, namely: i)behavioral observations/ratings by parents/caregivers(six studies), and ii) subtest scores from standardizedtest batteries assessing a variety of neurodevelopmentaldomains (three studies).

Neurodevelopmental profiles of FASD based onbehavioral observations/ratings by parents/caregiversThe Child Behavior Checklist (CBCL; five studies) andthe Behavior Rating Inventory of Executive Function(BRIEF; one study) have been used to identify a neurode-velopmental profile characteristic of FASD.

Child Behavioral Checklist (CBCL)Nash and colleagues [21] sought to determine if a behav-ioral profile distinguishes children with FASD (diagnosedaccording to the 2005 Canadian diagnostic guidelines;[1]) from typically developing children and children withADHD. The CBCL is a well-established standardizedparent/caregiver questionnaire utilized for evaluatingsocial competencies and behavioral problems in children6 to 18 years of age, and is comprised of a series of openended questions and a rating scale of 113 behavioraldescriptors. The authors utilized discriminant functionanalysis and Receiver Operating Characteristics curveanalyses to determine sensitivity and specificity of differ-ent item combinations. Findings revealed ten specificbehavioral characteristics captured by the CBCL (Table 1)had the potential to differentiate between children withFASD from children with ADHD and typically develop-ing control children, all 6 to 16 years of age. Specificitem combinations (Table 2) resulted in 86% (95% CI:77%–95%) sensitivity and 82% (95% CI: 72%–92%)specificity when children with FAS where compared totypically developing control children, and 70% (95% CI:58%–82%) to 81% (95% CI: 71%–91%) sensitivity and72% (95% CI: 61%–83%) to 80% (95% CI: 70%–90%) spe-cificity when children with FAS where compared to chil-dren with ADHD.Nash, Koren, and Rovet [22] replicated their earlier

study [21] using a larger sample and comparing childrenwith FASD (diagnosed according to the 2005 CanadianGuidelines; [1]) to children with ODD/CD, as well aschildren with ADHD and typically developing controlchildren in order to establish the specificity of the 10-item screening tool. All children ranged in age from 6 to18 years of age. Findings revealed the tool differentiatedchildren with FASD from control children with 98%(95% CI: 95%–100%) sensitivity and 42% (95% CI: 33%–51%) specificity, and from children with ADHD with89% (95% CI: 83%–95%) sensitivity and 42% (95% CI:33%–51%) specificity. However, sensitivity and specificitycould not be determined for discriminating childrenwith FASD from children with ODD/CD since only oneitem significantly differentiated these groups, namely“acts young”.From their preliminary investigations showing that

certain behaviors had the potential to identify childrenwith a high likelihood of having FASD, Nash and col-leagues [21, 22] proposed using this 10-item questionnaire




as a screening tool and coined it the “NeurobehavioralScreening Tool (NST)”. Based on the two studiesdiscussed above [21, 22], it was discerned that the NSThas the potential to delineate children with FASD fromchildren with ADHD and normally developing children.However, these two studies were limited in that theyretrospectively extracted items from the fully administeredCBCL, and their samples consisted of children aged 6 to18 only. The former limitation is noteworthy given thatthe CBCL is scored on a three-point scale (i.e., “not true”,“somewhat or sometimes true”, and “very true or oftentrue”); the authors of the NST collapsed the responses“somewhat or sometimes true” and “very true or oftentrue” and this can affect the classification accuracy. Thelatter limitation means that the behaviors noted in theNST cannot be assumed to be reflective of children withFASD outside this age range (i.e., less than 6 and over18 years of age).Accordingly, Breiner, Nulman, and Koren [23]

conducted a study in order to determine if the NSTcould be validated among a sample of children diag-nosed with FASD (according to the 2005 CanadianGuidelines; [1]), children with either a deferred diagnosisor for whom a diagnosis could not be confirmed, andnormally developing control children, all 4 to 6 years ofage. Three items (lie/cheat, steal at home, and stealoutside the home) were excluded from the analysis due

Table 1 Neurobehavioral Screening Tool (NST)

Items

1. Has your child been seen or accused of or thought to have acted tooyoung for his or her age?

2. Has your child been seen or accused of or is thought to bedisobedient at home?

3. Has your child been seen or accused of or is thought to lie or cheat?

4. Has your child been seen or accused of or is thought to lack guiltafter misbehaving?

5. Has your child been seen or accused of or is thought to havedifficulty concentrating, and can’t pay attention for long?

6. Has your child been seen or accused of or is thought to actimpulsively and without thinking?

7. Has your child been seen or accused of or is thought to havedifficulty sitting still, is restless or hyperactive?

8. Has your child been seen or accused of or is thought to display actsof cruelty, bullying or meanness to others?

9. Has your child been seen or accused of or is thought to steal itemsfrom home?

10. Has your child been seen or accused of or is thought to steal itemsfrom outside of the home?

Source: Nash and colleagues [21, 22]Note. Each item has a response option of ‘Yes’ or ‘No’

Fig. 1 Schematic diagram depicting the search strategy employed


Table

2Classificatio

naccuracy

oftheNeurobe

havioralScreen

ingTool

repo

rted

intheindividu

alstud

ies

Reference

Age

rang

e(years)

Com

parison

Itemsen

dorsed

Sensitivity

95%

CIa

Specificity

95%

CIa

Lower

Upp

erLower

Upp

er

Breine

ret

al.[23]

4to

6FA

SD(n=17)vs.D

eferred/Con

trols

(n=43)b

≥5items(item

s1,2,4–8;actsyoun

g,disobe

dien

t,lacksgu

ilt,d

ifficulty

concen

trating,

impu

lsivity,h

yperactive,cruelty)c

94%

88%

100%

96%

91%

100%

Hayne

set

al.[26]

6to

12Childrenbo

rnto

andreared

bymothe

rswith

depression

(n=49)

vs.C

ontrols(n=22)

≥6items(out

ofitems1–7;actsyoun

g,disobe

dien

t,lie/che

at,lacks

guilt,

difficulty

concen

trating,

impu

lsivity,hyperactive)

OR≥3items(out

ofitems

1,2,3,and4;actsyoun

g,disobe

dien

t,lie/che

at,lacks

guilt)

--

-100%

--

LaFrance

etal.

[24]

6to

17FA

SD(n=48)vs.C

ontrols(n=32)

≥6items(out


g,disobe

dien

t,lie/che

at,lacks

guilt,

difficulty

concen

trating,

impu


OR≥3items(out

ofitems

1,2,3,and4;actsyoun

g,disobe

dien

t,lie/che

at,lacks

guilt)

63%

53%

74%

100%

--

Childrenpren

atallyexpo

sedto

alcoho

lwho

didno

tmeetthe

criteria

foran

FASD

diagno

sis

(n=22)vs.C

ontrols(n=32)

≥6items(out


g,disobe

dien

t,lie/che

at,lacks

guilt,

difficulty

concen

trating,

impu


OR≥3items(out

ofitems

1,2,3,and4;actsyoun

g,disobe

dien

t,lie/che

at,lacks

guilt)

50%

37%

63%

100%

--

Nashet

al.[21]

6to

18FA

SD(n=30)vs.C

ontrols(n=30)

≥6items(out


g,disobe

dien

t,lie/che

at,lacks

guilt,

difficulty

concen

trating,

impu


86%

77%

95%

82%

72%

92%

FASD

(n=30)vs.A

DHD(n=30)

≥2items(out

ofitems1,4,and8;actsyoun

g,lacksgu

ilt,cruelty)

70%

58%

82%

80%

70%

90%

≥3items(out

ofitems1,4,8,9,and10;actsyoun

g,lacksgu

ilt,cruelty,

stealsfro

mho

me,stealsfro

mou

tsideho

me)

81%

71%

91%

72%

61%

83%

Nashet

al.[22]

6to

18FA

SD(n=56)vs.C

ontrols(n=53)

≥3items(out

ofall10items;actsyoun

g,disobe

dien

t,lie/che

at,lacks

guilt,

difficulty

concen

trating,

impu

lsivity,hyperactive,cruelty,stealsfro

mho

me,

stealsfro

mou

tsideho

me)

98%

95%

100%

42%

33%

51%

FASD

(n=56)vs.A

DHD(n=50)

≥2items(out

ofitems1,4,8,9,and10;actsyoun

g,lacksgu

ilt,cruelty,

stealsfro

mho

me,stealsfro

mou

tsideho

me)

89%

83%

95%

42%

33%

51%

FASD

(n=56)vs.O

DD/CD(n=61)

1item

(item

1;actsyoun

g)-

--

--

-

ADHDAtten

tionDeficitHyp

eractiv

ityDisorde

r,CD

Con

duct

Disorde

r,CI

Con

fiden

ceInterval,FASD

FetalA

lcoh

olSp

ectrum

Disorde

r,ODDOpp

osition

alDefiant

Disorde

ra Estim

ated

bythecurren

tau

thor,u

sing

abino

miald

istribution

bItisassumed

that

child

renwith

FASD

werecompa

redto

child

renforwho

madiag

nosiscouldno

tbe

confirm

edor

was

deferred

incombina

tionwith

controlchildren(m

etho

dsan

dresults

sections

wereinad

equa

teto

determ

ineifthisassumptioniscorrect)

c Item

s3,

9,an

d10

(lie/cheat,steala

tho

me,

andstealo

utside

theho

me)

wereexclud

edfrom

thean

alysisdu

eto

theinab

ility

toverifytheseite

msin

mostyo

ungchild

ren


to the inability to verify these items in most youngchildren. Using the seven remaining items, the authorsfound that the NST had 94% (95% CI: 88%–100%)sensitivity and 96% (95% CI: 91%-100%) specificity inidentifying children with FASD (Table 2). However, it isunclear from which group children with FASD werediscriminated (i.e., if the non-diagnosed group wascombined with the control children), as the methodsand results sections describing it are inadequate. Further,this study retrospectively extracted items from the CBCLin its entirety.More recently, LaFrance et al. [24] administered the

NST as a stand-alone instrument to parents/caregiversof children 6 to 17 years of age and thus, addressed thelimitation of collapsing items originally scored on athree-point scale [21–23]. Using the scoring approachpublished by Nash and associates [21], compared withnormally developing control children, the NST yielded63% (95% CI: 52%–74%) sensitivity and 100% (not pos-sible to estimate 95% CI) specificity for children withFASD (diagnosed according to the 4-Digit DiagnosticCode; [25]) and 50% (95% CI: 37%–63%) sensitivity and100% (not possible to estimate 95% CI) specificity forchildren prenatally exposed to alcohol who did not meetthe diagnostic threshold when assessed (Table 2). Thisstudy also assessed possible age- and sex-related differ-ences on the NST, by comparing 6–to 11-year oldchildren with 12–to 17-year old adolescents, and boysversus girls. For both the FASD group and the group ofchildren prenatally exposed to alcohol who did not meetthe diagnostic threshold, the NST showed highersensitivity among adolescents (71% [95% CI: 61%–81%]and 71% [95% CI: 59%–83%], respectively) when com-pared with children (54% [95% CI: 43%–65%] and 40%[95% CI: 27%–53%], respectively). For the FASD grouponly, the NST also had higher sensitivity among boyswhen compared with girls (71% [95% CI: 61%–81%] and56% [95% CI: 45%–67%], respectively). Specificity wasfound not to differ with respect to age and sex, as it was100% (not possible to estimate 95% CI) in all of thecomparisons. Lastly, the authors explored an alternativecumulative scoring option, with the endorsement of atleast four items resulting in 90% (95% CI: 83%–97%)sensitivity and 91% (95% CI: 85%–97%) specificity. Thisstudy is not only the first to administer the NST as astand-alone instrument, but is also the first to differenti-ate children prenatally exposed to alcohol who do notmeet the criteria for an FASD diagnosis from typicallydeveloping control children. The discrimination ofchildren prenatally exposed to alcohol who did not meetthe criteria for an FASD diagnosis helps to furtherestablish the specificity and discriminate validity of theNST. Nonetheless, it must be noted that this studyinvolved the retrospective administration of the NST in

a sample of children that had had already undergone afull diagnostic evaluation, thereby limiting the degree towhich the results can be said to establish the validity ofthe NST as a “screening” tool per se.In order to further establish the specificity of the NST,

Haynes, Nulman, and Koren [26] recently evaluated theinfluence of maternal depression – the most prevalentpsychiatric morbidity among women with difficultiesinhibiting their consumption of alcohol duringpregnancy [27] – on the previously identified behavioralpresentation of children with FASD [21, 22, 24] (diag-nosed according to either the 2005 Canadian diagnosticguidelines [1] or the 4-Digit Diagnostic Code [25]).Specifically, the investigators sought to determine if theNST resulted in any false positives among a sample ofchildren born to and reared by mothers with clinicaldepression and typically developing control children.None of the children with mothers suffering fromdepression scored positive on the NST (100% specificity,not possible to estimate 95% CI; Table 2). In fact, onlyone item (hyperactive) was found to be significantlyhigher in the group of children with mothers sufferingfrom depression, compared with the control children.In summary, the NST has demonstrated good sensitivity

(63% to 98%), but varying specificity (42% to 100%, withsome estimates being unfavorably low), and thus shouldstill be considered in the validation stage. It is importantto note that the NST is intended for screening purposesonly [21, 22], and given it is limited to overt behaviorsonly, its ability as a diagnostic tool is questionable since itdoes not fully capture all neurodevelopmental impair-ments seen among individuals with FASD. However, thereare few limitations of the available studies on the NST thatshould be noted. First, all of the studies evaluating the psy-chometric utility of the NST are plagued by small or mod-est at best, clinically-referred Canadian samples, thuslimiting generalizability of the above findings. Second, theNST has the inherent problem of providing the behavioralobservations of parent or parent substitutes, who by defin-ition are not masked to the child’s history and thusmay convey observations distorted by positive intent.Third, although a few of the studies investigating the NSTspecified whether the participants that made up the com-parison groups were screened for prenatal alcohol expos-ure, and subsequently excluded [21, 22], others did not[23, 24, 26].

Behavior Rating Inventory of Executive Function (BRIEF)Recently, Nguyen and colleagues [28] sought to determinewhether the BRIEF clinical scales, a parent/caregiver ques-tionnaire that consists of 86-items and eight empiricallyderived clinical scales assessing executive function andself-regulation in children 5 to 18 years of age, can distin-guish among the following four groups of children: 79


children prenatally alcohol-exposed with ADHD; 36children prenatally alcohol-exposed without ADHD; 90children with idiopathic ADHD (without prenatal alcoholexposure); and 168 typically developing control children.Prenatal alcohol exposure was defined as at least fourdrinks per occasion at least once per week or at least 14drinks per week during pregnancy. A discriminantfunction analysis revealed that the following four clinicalscales best distinguished the groups: i) Inhibit, which de-scribes a child’s ability to tune out irrelevant stimuli; ii)Emotional Control, which describes a child’s ability tomodulate emotional responses; iii) Working Memory,which describes a child’s ability to hold information inmind for the purpose of completing a task; and iv)Organization of Materials, which describes a child’s order-liness of work, play, and storage spaces. Classificationaccuracy was 71% (95% CI: 66%–76%) overall, with 67%(95% CI: 62%–72%) of children prenatally alcohol-exposedwith ADHD, 43% (95% CI: 38%–48%) children prenatallyalcohol-exposed without ADHD, 51% (95% CI: 46%–56%)of children with idiopathic ADHD, and 92% (95% CI:89%–95%) of typically developing control children classi-fied correctly.Although its use as tool to discriminate individuals

with FASD from other clinical populations is still in theexploratory stages, the BRIEF appears to distinguishalcohol-exposed children with ADHD from those withidiopathic ADHD, and thus may be useful as a screeningtool. However, based on the results presented above, theability of the BRIEF to identify children prenatallyalcohol-exposed without ADHD is limited.

Neurodevelopmental profiles of FASD based on subtestscores from a battery of standardized testsMattson and colleagues [29] sought to identify a neurode-velopmental profile of FASD using subtest scores from abattery of neurodevelopmental tests administered to indi-viduals heavily exposed to alcohol prenatally, defined asfour or more drinks per occasion at least once per weekor 13 or more drinks per week, and individuals with noprenatal alcohol exposure or minimal exposure, defined asno more than one drink per week on average and amaximum of two drinks per occasion. All participantswere between 7 and 21 years of age and subsequently cat-egorized based only on physical features, regardless oftheir exposure status. Classifications included “FAS”, de-fined as the presence of at least two of the three key facialfeatures (short palpebral fissures, smooth philtrum, andthin vermillion boarder) and either microcephaly (headcircumference ≤10th percentile) or growth deficiency(weight and/or height ≤10th percentile) or both; “NotFAS”; or “Deferred”, defined as the presence of at leastone key facial feature, or microcephaly and growthdeficiency, or microcephaly or growth deficiency and at

least one additional specified feature documented to beprevalent among those with FASD such as ptosis, andcamptodactyly. Twenty-two variables, derived from thesubtests of a battery of standardized tests, were selectedbased on their effect size in detecting the difference be-tween exposed and unexposed individuals.Two latent profile analyses were performed in order

to derive a discriminative profile. In both analyses, atwo-class solution fit better than a one-class solution– meaning that, based on the response means, it wasmore likely that there were two unobserved groups inthe sample used in each analysis. In the first analysis,exposed individuals who met the study criteria forFAS (n = 41) were compared with unexposed individ-uals categorized as Not FAS (n = 46); the resultingprofile had an overall classification accuracy of 92%(95% CI: 86%–98%), with 88% (95% CI: 81%–95%)sensitivity and 96% (95% CI: 92%–100%) specificity.In the second analysis, exposed individuals catego-rized as Not FAS or Deferred (n = 38) were comparedwith unexposed individuals categorized as Not FAS orDeferred (n = 60); the resulting profile had an overallclassification accuracy of 85% (95% CI:78%–92%), with68% (95% CI: 59%–77%) sensitivity and 95% (95% CI:91%–99%) specificity. The discriminative profile con-sisted of deficits in executive function, attention,spatial reasoning and memory, fine motor speed, andvisual motor integration (Table 3). In both analyses,individuals categorized as belonging to “Group 1” per-formed more poorly than those belonging to “Group 2”,with significantly more alcohol-exposed individuals in“Group 1” and significantly more unexposed individuals in“Group 2”. See Table 3 for the measures included in theprofile and neurodevelopmental domains assessed.In a subsequent study, Mattson and colleagues [30]

attempted to further refine their initial neurodevelop-mental profile [29] by i) reducing the number ofvariables included, ii) using a larger sample between 8and 17 years of age, and iii) including a clinical con-trast group. The same definitions of “heavily exposedto alcohol prenatally” and “no prenatal alcohol expos-ure or minimal exposure” were used as before [29].Based on clinical judgment and expertise, researchersselected 11 variables from the large test battery, fourof which overlapped with those selected in theprevious study [29] (Note: overlapping measures areindicated with an asterisk in Table 4).Three latent profile analyses were conducted. In all

three analyses, a two-class solution fit better than a one-class solution. In the first analysis, exposed individualswho met the study criteria for FAS (same criteria as theauthors previous study [29]; n = 79) were compared withunexposed individuals (n = 185) and the resulting profileyielded an overall classification accuracy of 76% (95% CI:


71%–81%), with 77% (95% CI: 72%–82%) sensitivity and76% (95% CI: 71%–81%) specificity. In the secondanalysis, exposed individuals who did not meet the cri-teria for FAS (n = 117) were compared with unexposedindividuals (n = 185); the resulting profile had an overall

classification accuracy of 72% (95% CI:67%–77%), with70% (95% CI: 65%–75%) sensitivity and 72% (95% CI:67%–77%) specificity. The third analysis comparing ex-posed individuals with and without FAS (n = 209) andindividuals with ADHD who were not exposed to alco-hol prenatally (as per the definition of prenatal alcoholexposure used by the authors; n = 74) led to a profilewith an overall classification accuracy of 74% (95% CI:69%–79%), with 60% (95% CI: 54%–66%) sensitivity and76% (95% CI: 71%–81%) specificity. The discriminativeprofile consisted of deficits in executive function,attention, and visual and spatial memory, with measuresof executive function most effectively distinguishingindividuals prenatally alcohol-exposed from those notexposed (Table 4). In all three analyses, significantly morealcohol-exposed individuals belonged to “Group 1” andsignificantly more unexposed individuals to “Group 2”(see Table 4 for the measures included in the profile andneurodevelopmental domains assessed).From a clinical perspective, the psychometric utility

of the profile of Mattson and colleagues [30] was notoptimal in discriminating those with FASD from thosewith ADHD – it was more accurate at identifying in-dividuals with ADHD than individuals with FASD.Further, it appears that a more limited test battery isnot equally as useful at distinguishing between

Table 3 Measures included in the profile and neurodevelopmentaldomains assessed by Mattson and colleagues [29]

Observed variable/measure Neurodevelopmentaldomain(s) measured

CANTAB Spatial Recognition MemoryPercent Correct (z-score)

Visual memory, spatialreasoning

CANTAB Spatial Span Length (z-score) Executive function, spatialreasoning, visual memory

CANTAB Spatial Working MemoryStrategy (z-score)

Executive function, spatialworking memory

CANTAB Spatial Working Memory TotalErrors (z-score)


D-KEFS Trail Making CombinedNumber/Letter (scaled score)

Executive function,sequencing

D-KEFS Trail Making–Switch versusNumber (scaled score)

Executive function, cognitiveflexibility

D-KEFS Trail Making–Switch versus Visual(scaled score)

Executive function

D-KEFS Trail Making–Switch Errors(scaled score)


D-KEFS Verbal Fluency Total Correct Letter(scaled score)

Executive function, fluency

D-KEFS Verbal Fluency Total CorrectCategory (scaled score)


D-KEFS Verbal Fluency Total CorrectSwitch (scaled score)


D-KEFS Verbal Fluency Second IntervalCorrect (scaled score)


D-KEFS Verbal Fluency Set Loss Errors(scaled score)

Executive function, setmaintenance

MVWM Time in Target Quadrant onProbe Trail (raw score)

Spatial learning

NES3 Animals Following subtest, NumberCorrect (raw score)

Sustained attention

NES3 Animals Repeating subtest, NumberCorrect (raw score)

Sustained attention

NES3 Animals Single subtest, NumberCorrect (raw score)

Sustained attention

Grooved Pegboard Test Dominant HandCompletion Time (z-score)

Fine motor

Grooved Pegboard Test Non-DominantHand Completion Time (z-score)

Fine motor

Progressive Planning Test MaximallyConstrained Total Score (raw score)

Executive function, planning

Visual Discrimination Reversal LearningTest Number of Reversals (raw score)


Visual Motor Integration Test Total(standard score)

Visual-motor

CANTAB Cambridge Neuropsychological Test Automated Battery, D-KEFSDelis-Kaplan Executive Function System, MVWM Morris Virtual Water Maze,NES3 Neurobehavioral Evaluation System 3

Table 4 Measures included in the profile and neurodevelopmentaldomains assessed by Mattson and colleagues [30]

Observed variable/measure Neurodevelopmental domain(s)measured

CANTAB Delayed Matching to SamplePercent Correct (z-score)

Short-term and long-term visualand spatial memory

CANTAB Intra-Extra Dimensional ShiftStages Completed (z-score)


CANTAB Intra-Extra Dimensional ShiftTotal Errors (z-score)


CANTAB Simple Reaction Time PercentCorrect Trials (raw score)

Attention, reaction time

CANTAB Spatial Working MemoryTotal Errors (z score)*


D-KEFS Color-Word InterferenceInhibition/Switching (scaled score)

Executive function, inhibitorycontrol, cognitive flexibility

D-KEFS Trail Making–Switch versusNumber (scaled score)*


D-KEFS 20 Questions Total InitialAbstraction (scaled score)

Executive function, planning,deduction

D-KEFS Tower Test Rule Violations PerItem Ratio (scaled score)

Executive function, planning

D-KEFS Verbal Fluency Total CorrectLetter (scaled score)*


D-KEFS Verbal Fluency Total CorrectSwitch (scaled score)*


*Indicates the measures that overlap with those selected in Mattson et al. [29]CANTAB Cambridge Neuropsychological Test Automated Battery, D-KEFSDelis-Kaplan Executive Function System


individuals with FASD and unexposed individuals as alarger test battery, as the sensitivity was reduced from88% in the first study [29] to 77% in the second study[30]. Lastly, although the classification rates weresignificant, a number of subjects were misclassified.Further, the two studies by Mattson et al. [29, 30]have a few limitations to note. First, coupled with thefact that the authors utilized test batteries thataccommodated the large age range and language vari-ations of their samples, the batteries used do not con-stitute a full clinical assessment battery typically usedin an FASD diagnostic clinics. As such, the test bat-teries lacked clinical sensitivity and likely excludedother measures that may have been useful in distin-guishing individuals with FASD from unexposedcontrols and other clinical populations. Second, thesamples were made up of participants clinicallyreferred for suspected problems or exposures andthus, prone to sampling bias, undermining the exter-nal validity of the findings. Third, the investigatorsonly included weaknesses in their neurodevelopmentalprofile and did not include relative strengths. Fourth,the classification of individuals as having FAS wasbased on physical traits only, and is not reflective ofhow FAS is classified elsewhere (see for example, theCanadian guidelines for diagnosis; [1]).Recently, Enns and Taylor [31] used logistic regression

to determine which neurodevelopmental variables aremost predictive of an FASD diagnosis. Studied were 180children and adolescents (5 to 17 years of age) prenatallyexposed to alcohol, 107 of whom received a diagnosis ofFASD according to the 2005 Canadian diagnostic guide-lines [1] and 73 who did not. The authors identified amodel that incorporated specific intelligence indices(verbal intelligence and working memory), academicachievements (spelling and math calculations), auditoryworking memory, and spatial planning correctly classi-fied 75% (95% CI: 70%–80%) of cases (sensitivity andspecificity were not reported). However, it was not clearif scaled scores were used in the model, and the mostobvious limitation of the study is that data was retro-spectively collected via a chart review of a clinically re-ferred sample. Further, given the retrospective nature ofthe study, the number of children and adolescentsassessed using each measure varied – however, the sam-ple size was not specified for the final profile. Althoughthe identified profile was able to differentiate individualsdiagnosed with FASD from those who were prenatallyexposed to alcohol but whom did not receive a diagnosisof FASD, the ability to differentiate individuals withFASD from unexposed individuals and individuals withother clinical populations remains unclear. See Table 5for the measures included in the profile and neurodeve-lopmental domains assessed by Enns and Taylor [31].

DiscussionBased on the studies reviewed above, it is clear that adefinitive neurodevelopmental profile of FASD has yetto be identified. However, the current literature has not-able clinical implications. First, behavioral ratings by pri-mary caregivers have the potential to be used in thedevelopment of a screening tool, which can be used toidentify those children most in need of a full multi-disciplinary diagnostic assessment. Second, a battery ofneurodevelopmental tests can be used to distinguishbetween children with FASD and typically developingchildren, children prenatally exposed to alcohol but whodo not meet the criteria for a diagnosis of FASD, as wellas children with ADHD. Overall, the results of thecurrent review support a stepwise approach the diagno-sis of FASD. A diagnosis of FASD has a number ofimportant benefits namely, participation in developmen-tal interventions, improved quality of life and a moreprosperous developmental trajectory in terms of socialfunctioning.Although a biomarker would be the most ideal method

for diagnosing cases of FASD, at this time observationaldata and neurodevelopmental testing are the most ap-propriate tools. Thus, the identification of a distinct neu-rodevelopmental profile that is pathognomonic of FASDwill assist in the: i) accurate identification of individualswith FASD, by adding to the resources available to clini-cians; ii) discrimination of FASD from other clinicalpopulations (i.e., differential diagnosis); iii) ascertain-ment of accurate prevalence estimates; iv) planning/de-velopment of appropriate targeted interventions forindividuals with FASD; and v) enhancement of clinicalservices to this population. Coupled with the fact thatthe neurodevelopmental assessment is both timeconsuming and costly [14], the current capacity of

Table 5 Measures included in the profile and neurodevelopmentaldomains assessed by Enns and Taylor [31]

Observed variable/measure Neurodevelopmental domain(s)measured

CMS Stories: Delayed/WMS-IVLogical Memory II

Auditory working memory

D-KEFS Tower: TotalAchievement

Executive function, spatial planning

WISC-IV Working Memory Index Working memory

WISC-IV Verbal ComprehensionIndex

Verbal intelligence

WRAT4 Math Calculations Academic achievement, mathematicalability

WRAT4 Spelling Academic achievement, basic readingand spelling ability

CMS Children’s Memory Scale, D-KEFS Delis-Kaplan Executive Function System,WISC-IV Wechsler Intelligence Scale for Children, Fourth Edition, WMS-IVWechsler Memory Scale, Fourth Edition, WRAT4 Wide Range Achievement Test,Fourth Edition


diagnostic services is also limited [32]. Thus, delineatingthe specific neurodevelopmental profile of FASD will notonly reduce the time it takes to fully assess an individual,but it will also assist in triaging children most in need ofa full clinical assessment [21, 22].Nevertheless, studies utilizing observational and/or

neurodevelopmental data to identify the presence of aunique neurodevelopmental profile of FASD are notwithout their limitations (e.g., confounding, and a lackof normative data with respect to FASD and mixedracial groups). In addition to the inherent data limita-tions, the two approaches currently used in determin-ing the neurodevelopmental profile of FASD are bothlimited in scope. For instance, the approach involvingobservations/ratings of parents/caregivers (i.e., theNST) is solely based on problem behaviors. However,individuals with FASD have a number of other devel-opmental impairments and behavioral manifestationsthat could be useful when delineating FASD fromother clinical populations. Further, the neurodevelop-mental profiles based on the subtest scores from abattery of standardized tests do not consider therelative strengths of individuals with FASD [11, 33].It should also be recognized that the studies reviewed

used different diagnostic guidelines for ascertainingcases of FASD. Given that it was recently reported thatexisting FASD diagnostic guidelines lack convergent val-idity and are limited in their concordance with respectto the specific diagnostic entities [34], the consequenceof this variation is that the profiles are essentially classi-fying different groups of affected individuals. Thus, theonly conceivable way to resolve this issue is for a stan-dardized common diagnostic approach to be developedand widely accepted. Only then will we be able to iden-tify whether a neurodevelopmental profile of FASDexists, and truly assess its classification function.Further, given the stigmatization associated with

alcohol use during pregnancy and the increased likeli-hood of underreporting [35], it is possible that the com-parison groups of typically developing control childrenused in the studies reviewed may contain some childrenprenatally exposed to alcohol, which is possible for ex-ample in studies of Mattson and colleagues [29, 30]given their definition of prenatal alcohol exposure. Con-sequently, the classification function of a particular pro-file could in fact be more robust than observed.Although it is clear that the identification of a neu-

rodevelopmental profile of FASD has a number ofnotable benefits, at least eight areas of future researchneed to be addressed before a neurodevelopmentalprofile is defined and put into practice. The first con-cerns testing the profile on larger, more diverse sam-ples, as well as in general population screeningsettings (i.e., among population-based samples).

Second, the profile’s ability to differentiate childrenwith FASD from other clinical populations (e.g., otherthan idiopathic ADHD, without prenatal alcoholexposure) needs to be determined. Third, potentialgender and age differences need to be explored, andthe cross-cultural utility of the profile needs to beestablished. Fourth, a broader, more comprehensivearray of neurodevelopmental domains needs to beevaluated. Fifth is the possibility that individuals withFASD exhibit more than one neurodevelopmentalprofile should be explored. For example, a distinctprofile could exist for each diagnostic category. Sixth,future studies need to control for adverse prenatalexposures such as maternal smoking and drug useduring pregnancy, maternal and paternal psychopa-thologies, and postnatal experiences including abuseand neglect. Seventh is the possibility that some ofthe associated neurodevelopmental symptoms wereinherited from parents (e.g., a math disability) andnot strictly attributable to the prenatal alcohol expos-ure. Eighth, it is possible that individual differences infactors that influence the consequences of prenatalalcohol exposure may interfere with the identificationa unique neurodevelopmental profile of FASD giventhat susceptibility to prenatal alcohol exposuredepends on the genotype of the fetus [36] and thedevelopmental stage at the time of exposure, and thatthe manifestations of abnormal development increasein frequency and degree as dosage increases (as perthe principles of teratogenesis; [37, 38]). Accordingly,genetic factors/differences in fetal susceptibility toalcohol and information on dosage and timing ofexposure should also be taken into considerationwhen identifying and validating a neurodevelopmentalprofile of FASD. It is likely that many of these areasof future research will only be achievable if and whenlarge detailed datasets are developed containing dataon individuals with FASD diagnosed using a commondiagnostic guideline, which will allow for certain vari-ables (e.g., experience of postnatal adversities) to becontrolled for.However, given that the outcomes of prenatal alcohol

exposure depend on a number of factors (e.g., genetics,health, alcohol metabolism, polysubstance exposure,timing of exposure [39–41]), as well as the fact thatFASD is associated with multiple comorbid mental dis-orders [42–44], it should be acknowledged that FASDmay in fact have a complex phenotype and a pathogno-monic neurodevelopmental profile of FASD may notexist. It is possible that FASD has a pleiotropic pheno-type (i.e., one cause (prenatal alcohol exposure) resultsin many outcomes); if this is the case it will negate theexistence of a neurodevelopmental profile unique tothose with FASD.


Strengths and limitationsThe current literature review has a number of notablestrengths, namely the comprehensive search strategies,strict inclusion and exclusion criteria, and the critical ap-proach to presenting the existing neurodevelopmentalprofiles of FASD. However, it is important to acknowledgethat this review is limited to those profiles that were ac-companied by an evaluation of their classification func-tion. Nevertheless, there are profiles that show somepromise that were not eligible for inclusion in the currentreview (e.g., Nash et al. [8] and Stevens et al. [45]).

ConclusionsThis systematic review elucidates the need for additionalwell-conducted research investigating the existence of aneurodevelopmental profile of FASD. Although researchin this area is limited and a definitive neurodevelopmentalprofile of FASD remains to be established, the benefits ofidentifying a pathognomonic neurodevelopmental profileare noteworthy. It is likely that a neurodevelopmentalprofile of FASD that includes both behavioral observa-tions/ratings and performance-based measures ofneurodevelopment will be the most comprehensive and assuch, future studies should include measures covering abroad array of neurodevelopmental and behavioraldomains.

Endnotes1Sensitivity and specificity are measures of a binary clas-

sification test’s accuracy. Sensitivity is the probability of apositive test result among those with the condition (i.e.,the percentage of individuals who are correctly identifiedas having the condition), while specificity is the probabilityof a negative test result among those without the condi-tion (i.e., the percentage of individuals who are correctlyidentified as not having the condition).

AbbreviationsADHD: Attention Deficit Hyperactivity Disorder; ARBD: Alcohol-Related BirthDefects; ARND: Alcohol-Related Neurodevelopmental Disorder;CANTAB: Cambridge Neuropsychological Test Automated Battery;CD: Conduct Disorder; CMS: Children’s Memory Scale; D-KEFS: Delis-KaplanExecutive Function System; FAS: Fetal Alcohol Syndrome; FASD: Fetal AlcoholSpectrum Disorder; MVWM: Morris Virtual Water Maze; ND-PAE: Neurobehavioral Disorder Associated with Prenatal Alcohol Exposure;NES3: Neurobehavioral Evaluation System 3; NST: Neurobehavioral ScreeningTool; ODD: Oppositional Defiant Disorder; pFAS: Partial Fetal AlcoholSyndrome; WISC-IV: Wechsler Intelligence Scale for Children, Fourth Edition;WMS-IV: Wechsler Memory Scale, Fourth Edition; WRAT4: Wide RangeAchievement Test, Fourth Edition

AcknowledgementsNot applicable.

FundingNo external funding was sought for the current study.

Availability of data and materialsData sharing is not applicable to this article as no datasets were generatedor analysed during the current study.

Authors’ contributionsMs. Lange led the conception and design of the study, acquired the data,analyzed and interpreted the data, wrote the first draft of the manuscript,and revised the manuscript; Drs. Rovet and Rehm contributed to datainterpretation, and have revised the manuscript critically for importantintellectual content; and Dr. Popova contributed to the conception anddesign of the study, supervised the analysis and interpretation of the data,and revised the manuscript critically for important intellectual content. Allauthors read and approved the final manuscript.

Ethics approval and consent to participateNot applicable.

Consent for publicationNot applicable.

Competing interestsThe authors declare that they have no competing interests.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in publishedmaps and institutional affiliations.

Author details1Institute for Mental Health Policy Research, Centre for Addiction and MentalHealth , Toronto, ON, Canada. 2Institute of Medical Science, University ofToronto, Toronto, ON, Canada. 3Neuroscience and Mental Health Program,The Hospital for Sick Children, Toronto, ON, Canada. 4Department ofPediatrics, University of Toronto, Toronto, ON, Canada. 5Dalla Lana School ofPublic Health, University of Toronto, Toronto, ON, Canada. 6Institute ofClinical Psychology and Psychotherapy & Center of Clinical Epidemiologyand Longitudinal Studies, Technische Universität Dresden, Dresden, Germany.7Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON,Canada.

Received: 1 February 2017 Accepted: 15 June 2017

References1. Chudley AE, Conry J, Cook JL, Loock C, Rosales T, LeBlanc N. Fetal alcohol

spectrum disorder: Canadian guidelines for diagnosis. CMAJ. 2005;172Suppl 5:S1–21.

2. Hoyme HE, Kalberg WO, Elliott AJ, Blankenship J, Buckley D, Marais AS, et al.Updated clinical guidelines for diagnosing fetal alcohol spectrum disorders.Pediatrics. 2016;138:e20154256.

3. Cook JL, Green CR, Lilley CM, Anderson SM, Baldwin ME, Chudley AE, et al.Fetal alcohol spectrum disorder: a guideline for diagnosis across thelifespan. CMAJ. 2016;188(3):191–7.

4. American Psychiatric Association. Diagnostic and statistical manual ofmental disorders, 5th edition: DSM-5. Washington, DC: American PsychiatricAssociation; 2013.

5. Kable JA, O’Connor MJ, Olson HC, Paley B, Mattson SN, Anderson SM, et al.Neurobehavioral disorder associated with prenatal alcohol exposure(ND-PAE): Proposed DSM-5 diagnosis. Child Psychiatry Hum Dev. 2016;47(2):335–46.

6. Aragón AS, Coriale G, Fiorentino D, Kalberg WO, Buckley D, Gossage JP, et al.Neuropsychological characteristics of Italian children with fetal alcoholspectrum disorders. Alcohol Clin Exp Res. 2008;32(11):1909–19.

7. Kodituwakku PW, Handmaker NS, Cutler SK, Weathersby EK, Handmaker SD.Specific impairments in self-regulation in children exposed to alcoholprenatally. Alcohol Clin Exp Res. 1995;19(6):1558–64.

8. Nash K, Stevens S, Rovet J, Fantus E, Nulman I, Sobara D, et al. Towardsidentifying a characteristic neuropsychological profile for fetal alcoholspectrum disorders: 1. Analysis of the Motherisk FASD Clinic. J Popul TherClin Pharmacol. 2013;20(1):e44–52.

9. Rasmussen C, Horne K, Witol A. Neurobehavioral functioning in childrenwith fetal alcohol spectrum disorder. Child Neuropsychol. 2006;12(6):453–68.

10. Kodituwakku PW. Neurocognitive profile in children with fetal alcoholspectrum disorders. Dev Disabil Res Rev. 2009;15:218–24.


11. Mattson SN, Crocker N, Nguyen TT. Fetal alcohol spectrum disorders:Neuropsychological and behavioral features. Neuropsychol Rev.2011;21(2):81–101.

12. Bastons-Compta A, Astals M, Garcia-Algar O. Foetal alcohol spectrumdisorder (FASD) diagnostic guidelines: A neuropsychological diagnosticcriteria review proposal. J Neuropsychopharmacol Ment Health.2016;1(2):e104.

13. Chudley AE. Fetal alcohol spectrum disorder: Counting the invisible –mission impossible? Arch Dis Child. 2008;93(9):721–2.

14. Popova S, Lange S, Burd L, Chudley AE, Clarren SK, Rehm J. Cost of fetalalcohol spectrum disorder diagnosis in Canada. PLoS One. 2013;8(4):e60434.

15. McLennan JD. Misattributions and potential consequences: The case ofchild mental health problems and fetal alcohol spectrum disorders. Can JPsychitry. 2015;60(12):587–90.

16. Chasnoff IJ, Wells AM, King L. Misdiagnosis and missed diagnoses in fosterand adopted children with prenatal alcohol exposure. Pediatrics. 2015;135(2):264–70.

17. Astley SJ, Clarren SK. Diagnosing the full spectrum of fetal alcohol-exposedindividuals: Introducing the 4-digit diagnostic code. Alcohol Alcohol. 2000;35(4):400–10.

18. Streissguth AP, Bookstein FL, Barr HM, Press S, Sampson PD. A fetal alcoholbehavior scale. Alcohol Clin Exp Res. 1998;22(2):325–33.

19. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al.The PRISMA statement for reporting systematic reviews and meta-analysesof studies that evaluate health care interventions: explanation andelaboration. PLoS Med. 2009;6(7):e1000100.

20. Jones KL, Smith DW. Recognition of the fetal alcohol syndrome in earlyinfancy. Lancet. 1973;2:999–1001.

21. Nash K, Rovet J, Greenbaum R, Fantus E, Nulman I, Koren G. Identifying thebehavioural phenotype in fetal alcohol spectrum disorder: sensitivity,specificity and screening potential. Arch Womens Ment Health.2006;9(4):181–6.

22. Nash K, Koren G, Rovet J. A differential approach for examining thebehavioral phenotype of fetal alcohol spectrum disorders. J Popul Ther ClinPharmacol. 2011;18(3):e440–53.

23. Breiner P, Nulman I, Koren G. Identifying the neurobehavioral phenotype offetal alcohol spectrum disorder in young children. J Popul Ther ClinPharmacol. 2013;20(3):e334–9.

24. LeFrance MA, McLachlan K, Nash K, Andrew G, Loock C, Oberlander TF, etal. Evaluation of the Neurobehavioral Screening Tool in children with fetalalcohol spectrum disorders (FASD). J Popul Ther Clin Pharmacol. 2014;21(2):e197–210.

25. Astley S. Diagnostic Guide for Fetal Alcohol Spectrum Disorders: The 4-DigitDiagnostic Code. 3rd ed. Seattle, Washington, DC: University of WashingtonPublication Services; 2004.

26. Haynes K, Nulman I, Koren G. Fetal alcohol spectrum disorder and theneurobehavioural screening tool: evaluating the effect of maternaldepression. J Popul Ther Clin Pharmacol. 2014;21(3):e387–94.

27. Procopio DO, Saba L, Walter H, Lesch O, Skala K, Schlaff G, et al. (2013).Genetic markers of comorbid depression and alcoholism in women. AlcoholClin Exp Res. 2013;37(6):894–904.

28. Nguyen TT, Glass L, Coles CD, Kable JA, May PA, Kalberg WO, et al. Theclinical utility and specificity of parent report of executive function amongchildren with prenatal alcohol exposure. J Int Neuropsychol Soc. 2014;20(7):704–16.

29. Mattson SN, Roesch SC, Fagerlund A, Autti-Rämö I, Jones KL, May PA, et al.Toward a neurobehavioral profile of fetal alcohol spectrum disorders.Alcohol Clin Exp Res. 2010;34(9):1640–50.

30. Mattson SN, Roesch SC, Glass L, Deweese BN, Coles CD, Kable JA, et al.Further development of a neurobehavioral profile of fetal alcohol spectrumdisorders. Alcohol Clin Exp Res. 2013;37(3):517–28.

31. Enns LN, Taylor NM. Factors predictive of a fetal alcohol spectrum disorder:Neuropsychological assessment. Child Neuropsychol. 2016. [Epubahead of print].

32. Clarren SK, Lutke J, Sherbuck M. (2011). The Canadian Guidelines and theInterdisciplinary Clinical Capacity of Canada to Diagnose Fetal AlcoholSpectrum Disorder. J Popul Ther Clin Pharmacol. 2011;18(3):e494–9.

33. Greenbaum R, Nulman I, Rovet J, Koren G. The Toronto experience indiagnosing alcohol-related neurodevelopmental disorder: a unique profileof deficits and assets. Can J Clin Pharmacol. 2002;9(4):215–25.

34. Coles CD, Gailey AR, Mulle JG, Kable JA, Lynch ME, Jones KL. A ComparisonAmong 5 Methods for the Clinical Diagnosis of Fetal Alcohol SpectrumDisorders. Alcohol Clin Exp Res. 2016;40(5):1000–9.

35. Lange S, Shield K, Koren G, Rehm J, Popova S. A comparison of theprevalence of prenatal alcohol exposure obtained via maternal self-reportsversus meconium testing: a systematic literature review and meta-analysis.BMC Pregnancy Childbirth. 2014;14:127.

36. Eberhart JK, Parnell SE. The genetics of fetal alcohol spectrum disorders.Alcohol Clin Exp Res. 2016;40(6):1154–65.

37. O’Leary-Moore SK, Parnell SE, Lipinski RJ, Sulik KK. Magnetic resonance-based imaging in animal models of fetal alcohol spectrum disorder.Neuropsychol Rev. 2011;21(2):167–85.

38. Sulik KK. Fetal alcohol spectrum disorder: pathogenesis and mechanisms.Handb Clin Neurol. 2014;125:463–75.

39. Day J, Savani S, Krempley BD, Nguyen M, Kitlinska JB. Influence of paternalpreconception exposures on their offspring: through epigenetics tophenotype. Am J Stem Cells. 2016;5(1):11–8.

40. Eberhart JK, Parnell SE. The Genetics of Fetal Alcohol Spectrum Disorders.Alcohol Clin Exp Res. 2016;40(6):1154–65.

41. May PA, Gossage JP. Maternal risk factors for fetal alcohol spectrumdisorders: Not as simple as it might seem. Alcohol Res Health.2011;34(1):15–26.

42. Burd L, Klug MG, Martsolf JT. Fetal alcohol syndrome: neuropsychiatricphenomics. Neurotoxicol Teratol. 2003;25(6):697–705.

43. Lange S, Rehm J, Anagnostou E, Popova S. Prevalence of externalizingdisorders and autism spectrum disorder among children with fetal alcoholspectrum disorder: systematic review and meta-analysis. Biochem Cell Biol.2017; [Epub ahead of print].

44. Popova S, Lange S, Shield K, Mihic A, Chudley AE, Mukherjee RAS, et al.Comorbidity of fetal alcohol spectrum disorder: a systematic review andmeta-analysis. Lancet. 2016;387(10022):978–87.

45. Stevens SA, Nash K, Fantus E, Nulman I, Rovet J, Koren G. Towardsidentifying a characteristic neuropsychological profile for fetal alcoholspectrum disorders – 2. Specific caregiver- and teacher-rating. J Popul TherClin Pharmacol. 2013;20(1):e53–62.

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